Posted
by
ScuttleMonkey
on Wednesday March 29, 2006 @01:26PM
from the ghost-cars dept.

Belfegor writes "The PBS series Nova has a great feature on their website, regarding the coverage of the DARPA-sponsored 'Robot Race' in which driverless vehicles 'competed' in a 130-mile race across the Mojave Desert. The full show is available on the website, and besides that they have plenty more information about the robotics behind the challenge, and also some pretty cool out-takes from the show."

Yep. That was a big question mark in my mind as I watched the show last night. As soon as the first vehicle left the gate, I had to wonder, "What's going to happen if one of them catches up to the vehicle in front of them?" Passing a moving object is not like avoiding stationary objects -- which is all the qualifying course contained.Surprisingly, Stanley seemed to have no trouble at all passing Highlander, but I wonder how much of that was just pure luck (and the fact that it happened during a stretch wher

"I wonder how much of that was just pure luck (and the fact that it happened during a stretch where the trail was much wider than in many other spots)."

Yeah, it would have been interesting to see what would happen if Stanley had caught up to Highlander at a spot where there wasn't room to pass. Would it believe that Highlander was a stationary object and stop moving, thinking there was no way to proceed, or would it just have followed behind Highlander?

PBS broadcast that show last night. While I realise that is is a little 2001 to actually watch a program when it is braodcast, I did. And I really enjoyed it. I am hardly current on the status of autonomous robotics and I was pleasantly surprised by how far along the technology is. 130 miles through the dessert using only GPS and local sensors is a pretty amazing feat, and that course was tough. It features mountain switchbacks, tunnels and other hazards. If you even have a passing interest in robotics I recommend watching the show.

The interesting thing for me is that the method we use (our eyes) was too difficult for machines. That's why all those robots used lasers, and other techniques. We've come far, but we still have a long way to go.

This was a fascinating program. It would have been nice if the Stanford team divulged more of their ideas, what software languages and designs they used etc. It looked like they were doing a Bayesian classification on combined laser ranging and video on the terrain ahead. Doing that for 1 image is complicated enough. Doing 10+/sec is mindblowing. The control system moderated the vehicle's need to follow a prescribed path with how safe the path was. Amazing stuff, very elegant. Pretty much done with a stock

I agree that more detail would have been preferable. However, I expect the producers have to contend with trying to make this show appeal to a broader viewership than the typical/. geeks like you or I.

Does anyone have any links that contain more gory details about the Stanford effort?

Do a google search on Sabastian Thrun, he was the team lead for Stanford, and formally at CMU (what a non-coincidence). Most of the software they used on Stanly (Stanford's bot) was either written by Sebastian in his former research or taken from experience gained on CMU's team the previous year. The ladar mapping he used, I know I saw on some former page of his that had all the gory algorithm details. It might just take a little bit of searching. He also has a c library out there somewhere that does a lot of this stuff, but I can't seem to find it now.

> Most of the software they used on Stanly (Stanford's bot) was either written by Sebastian in his former research or taken from experience gained on CMU's team the previous year.[...]> BTW, I wasn't on Stanford's team, but I was on another finalist team.

Nice try, I wasn't on CMU either. No I was on a team that actually had to work for every dime they spent on the vehicle.

I'm not stating anything false. Read his research and when it took place. The core stuff all came from CMU or Sebastian in previous efforts (like I stated). Now once at Stanford they changed how they did things entirely and wrote a ton of code to make everything play much nicer than CMU's platform. Stanly was much smarter than either of the two CMU bots.

> Now once at Stanford they changed how they did things entirely and wrote a ton of code to make everything play much nicer than CMU's platform.

This sounds a little bit more like that, what I have heard. I've read, that they throw away most of the code and rewrote a large deal. E.g the classification of driveable terrain by the laser scanner was rewritten and learned. AFAIK, most of what has been published (and to what you pointed) is fairly generic stuff.

"To the best of my knowledge, it has not been published how they learned the far range vision based on the near range laser scanner, which, to my eyes, is the most interesting part of the project."

They didn't use the near range laser scanner for the far range vision. They had a color camera they used. That was what was used to get those Red/Green video's/pictures you see on Nova's site. None of the competitors used the SICK Lasers for anything more than 25 meters, because they simply didn't work past th

It was a good show. One nifty bit of engineering from the Stanford team was to overlay a video camera image over laser-generated map, use a color-matching system to determine what colors of the video were level and safe to drive on, and then extrapolate what areas of the video image were safe.The main difficulty that I see, going forward, is that the laser-rangefinder systems that these robots all relied on all function by looking for obstacles and attempting to avoid them. They can spot vertical anomalie

Since you said "windy" I read it as "windy" (ie. gusts of wind). I wonder how well these things can compensate for THAT. I bet they have a long way to go as far as "feeling" the grip on the road and drag/body roll of the chassis like a human does.

Worse, the MITRE team was killed by the wind, or more accurately by dust devils. they kept having dust devils blow in front of the sensors, causing the vehicle to make an emergency avoidance manuver (oh no! Something jumped in front of me!). One of these manuvers left the vehicle in a bush, unable to move because it couldn't find a clear way out of the bush.

I caught the show yesterday also.I was really happy Stanford won the competition. The "red" team with two entries (from Carnegie Mellon?) also finished but were behind on time... the thing is though not only was Stanford's win absolute, they also did it much "smarter".

Stanford took an approach of focusing on software, to make their vehicle more smart. They gave it the course, but left it up to the vehicle to decide how fast to go and the specifics of how soon to turn, etc.

Unlike Carnegie's "H1ghlander" and "Sandstorm", Stanford's "Stanley" VW Touareg had no fancy motion compensated sensors and the team didn't flesh out the race course with more GPS data and tell the vehicle how fast it could drive in certain areas. Stanley's software did all that on the fly.

Also, the SuperDAD Toyota pickup looked like it had a tenth of the tech of Stanley but it was doing almost as well. If only the laser sensor hadn't detached itself from the roof.

Yes, since one race really says a lot about which one is better. Let's look at the situation a few years from now and then make judgements. After all, CMU beat everyone the previous year. Plus, Stanford's team was basically a CMU team if you look at the composition of the team. Plus, using "0wn3d" at all was so 1997.Who cares though. Look at the improvement from two years ago to this past race. Now we have (forgive me if I forget the details) 5-6 vehicles that finished the race? That says great things about

True. There was so much hype surroung "Red Storm" and how it would p0wn the rest of the field before GC-1. Then during the trials, their Hummer tipped over because it took a curve too fast (d'oh!! where's the linkage between the wheel turning system and the speed system?). And in the race, it almost caught fire because 1 wheel got stuck and the other spun freely; the system controlling the engine just kept increasing the RPM, with the eventual result that the tires melted and flew off, and the controllers h

it is interesting just how involved the contestants are. This contest is their life. They mentioned several times in the show how many months of long workdays they spent to build and program these cars. And, then, who owns the work? Do they at least get patent recognition on some of the innovations? Some of the software they talked about was truly seriously cool stuff.

Sidenote: One hour of Nova or Frontline is like watching 5 days worth of "learning" and "discovery" shows elsewhere. It's amazing how good some of these shows are.

I love PBS documentaries man. You can learn sooo much from them in a nice little narrated package.

Maybe all these guys are geniuses and get grants to work on the stuff. Maybe university supported or something like that. Or! They make their money in half a year, and build robot cars the rest of the time.

Most (or many) universities make you sign away your rights to a patent for something you created on "university" time with university funds and equipment. It's one of the many political battlegrounds on campus in higher education these days. "How do you define what was done on whose time?" "Just because I work for the university doesn't mean that everything I do belongs to the uni", etc. etc.

I would wager that Stanford would be on the high ground if it came down to a legal battle.

They'll get patent recognition if they, you know, filed any patents. These teams can do whatever they want with any innovations they make. Many of them, especially the school based teams, operate under grants from other agencies which might have limitations on who owns or can patent what. However, each team makes the choice about where their funding comes from and what strings are attached to it.

Most of the successful teams had significant numbers of paid employees. Stanford had about sixty people back at Volkswagen working on the hardware. CMU had a huge headcount; they had more than fifty people on site at the Speedway, including people on the payrolls of Lockheed, Caterpillar, and other vendors. Oshkosh Truck was all paid employees.
Didn't talk to the Grey Team much, but they were paid by some Insurance company.

The big breakthrough was Stanford's texture vision system. I was very impressed

A minor correction... Stanford actually had 60 people total on the team. There were 9 people from VW working on the vehicle. You can see a list of all of the team members at our website [stanfordracing.org].

My point on this is that some key components went from being expensive one-offs to commercial products in a year, because Grand Challenge entrants pushed on the vendors. That, for DARPA, was a big win. In a few years, the hardware side of automatic driving will be a total non-problem. That's a big help for researchers; you spend too much time on necessary but mundane stuff.

To answer your question regarding who owns what. I can't speak for the large University teams because they are just in a different universe as the rest of us were. Most teams didn't bother filling out patents because we were all just too damn busy. What we do rely on is our IP though. I was on a finalist team and we did write some pretty cool software that we are trying to do some stuff with on another project now. We own all the code (we wrote it). CMU and Stanford are a different beast altogether.

DARPA competitions encourage innovation in technology. Technology which may well end up on the battlefield some day. Not necessarily a bad thing if it prevents the loss of life, but after viewing the aforementioned film, I've got to thinking about how improved technology may be encouraging to those who would start wars. Why We Fight goes a ways toward exploring the military-industrial complex, congress' complicity (i.e. parts of a bomber are made in all 50 states, any representative p

As a student at Carnegie Mellon who has discovered the extent of his school's ties to development (had I known prior... and no, CMU is not unique in this regard, the problem is everywhere) of military products and has since spoken out against them a few times, thank you for realizing that this DARPA stuff isn't all it's cracked up to be.I'm perhaps one of four people (an exaggeration, I hope) on my campus that isn't gung-ho about helping the DOD build driverless vehicles, and it's lonely at times.

As an alumnus of Carnegie Mellon, it was great to see the coverage. I did not realize that a lot of the Stanford team came from CMU; certainly says a lot about our robotics dept. Red is certainly a powerhouse there, and congrats that the two vehicles came in second and third.

I will say, I was impressed, and surprised that I did not see an article on it at/.. I believe there was one last year.

I will say, that aside from "Stanley" winning the race on completion and time, I also believe that Stanley was the best technology. The H1lander and friend were micromanaged, and there were two vehicles that had different strategies (the tortoise and the hair) and it took almost the whole 2 hours of a team of people to map out the course and program the robots. They then added the fudge factor for human error with the fast and slow strategies.

Stanley was programmed in minutes of receiving the map, and it calculated its speed dynamically on its own. Stanley had "adaptive vision" which overlaid laser, video, and other sensory data to create a dynamic field of view of what was safe to drive through.

Now, what shocked me, was that so many teams finished this year. Nobody got past 7 or 9 miles last year, and many vehicles passed the entire 132 mile trip this year. Watching the vehicles drive was impressive. Most of the time, they appeared to be manned.

The course was not easy, by any stretch of the imagination. With the success of Stanley, I believe that this will increase the adaptive and learning capabilities in current software controlled systems. Currently, software is brute forced into trying to accommodate all possible logical conditions, which is impossible, and often just wrong.

The Red team (CMU) basically preprogrammed their robots before the race by looking at satellite maps of the race course. I thought in essence this was cheating but I suppose it was not against the rules. The Blue Team (Stanford) had a better software solution where their robot would essentialy drive and learn on the fly. I'm glad to see Stanley won because this is the technology needed for automated driving, imagine using the Red team's solution and have to preprogram you car? What's the point?

I'm glad to see Stanley won because this is the technology needed for automated driving, imagine using the Red team's solution and have to preprogram you car? What's the point?

Exactly. I believe that the Stanley approach was more "real life" for what we do now, and what will be done in the future. When I go on a trip, or even go to somewhere locally where I don't know the exact location of where I go, I at least get the address and correlate it to something I do know. With the ease and availability of Go

Sorry to break up the party, but the second race was MUCH easier then the first. For the first 7 or 8 miles, each vehicle was in a dry lakebed. Comapre this to the ravines and washes that were in the first 7 or 8 miles of the last course.Why did they make it easier? My personal theory is the act of congress that calls for 2/3 of the armed forces to be autonomous vehicles by 2008 (or something of the sort; I'm probably wrong about the date).

I hadn't heard about it being for an autonomous gun platform. I watched the show last night and they presented it as purely for supply transports. They specifically mentioned Jessica Lynch and how she was just a truck driver who should never of been exposed to combat. They also mentioned that the DOD want's 1/3rd of their transport trucks to be autonomous within 10 years.

They specifically mentioned Jessica Lynch and how she was just a truck driver who should never of been exposed to combat.

She should have not volunteered for such a dangerous job.

I have a pet peeve with sob stories about how people enter known dangerous jobs, especially the military, where their existence is to be disposable to help the poor people of Iraq and ensure the economic welfare of the people back home.

Now, the initial invasion of Iraq is at best controversial. The continued occupation with no plan

What struck me about that comment regarding Jessica Lynch is that she was resupplying the frontline. That means she was driving an armoured truck to where guys (and girls) are actively engaged in firefights but her exposure to danger was the concern. Of course, anyway that we can have fewer people in harm's way in a positive but I found it unsettling that the battle line soldiers were mentioned as a throw-away in order to frame their argument.

I came into the show - in glorious HD, no less (PBS has great HD content!) - a little late, so I missed the Jessica Lynch reference.But I do understand the desire to attempt to make resupply trucks autonomous. I'm not entirely sure it's really possible... but I do understand the desire.

Modern militaries consume enourmous amounts of supplies, and those supplies are big, bulky, and heavy - and more often than not, highly explosive.

The main gun round for an M1A1 tank is around 200mm in diameter, weighs ~23kg,

"Another interesting point is that it seems to me that this is the development arena for the military's new autonomously roving gun platform."At some point this may be true, but more immediately this is the development arena for the military's new autonomous supply delivery system. If you look at the people that are most often getting attacked it's the supply caravans. If we didn't have to have people in those vehicles then the loss when a caravan is attacked is much less. Just because we can make a robot t

Hell yeah! Now instead of having friends or parents drive us everywhere, our cars can! And secondly... if I talk to my car, it just keeps bitching about low oil pressure. I told it to stop whining and go complain to the auto-shop. But the automated system at the shop accidently ate my car. Poor thing...

Shouldnt we be all seeing fully functional independent robots by now?The robotics is taking a long time to mature.*very very* long timeI believe the problem is that only small set of individual professors and small group of students cannot achieve huge breakthroughs in engineering.Creating an Atom Bomb was just engineering (since sustained reaction was experimentally proved in 1933 itself).But how many people could do it?It took a huge set of scientists (*read - not engineers) and a huge set of engineers wo

You sound like you are really ready for the planet to be overtaken by robots.

While the fact that so "few" (I am not sure of the validity of that statement)are working on improving robotics, you have to realize the massive task that it is to translate reality into a machine. And then... for that machine to independently make a decision based on the generalizations of their enviroment.

What would a fully functional independent robot do? How would it improve your lifestyle? What is that worth to you, as a consumer? When you can make a valid business case based on good answers to those questions, the robots will come out of the woodwork.

In some arenas, the technology already exists. Roomba vacuums are fully functional independent robots. You can get (for a price, and with limited capability) robot lawn mowers. Some subway systems use automated trains; they're fully functional and independe

Really good documentary! Seriously, you know you are a TRUE nerd when you witness an autonomous vehicle actually complete a race like this... and a tear comes to your eye! Really, I got misty-eyed watching this!!

What do you do in the future when one of these is mass-produced and forgets its turn signal and cuts you off?
Do you scream and give it the finger?
Throw rocks at it?
Run it off the road?
Launch a homing missile at it?
Any way around it, driverless vehicles will have no rights in our future society!
Who will speak up for the robots?

What do you do in the future when one of these is mass-produced and forgets its turn signal and cuts you off?

Finally, all my knowledge aquired over the years becomes extremely useful!

I know this one... What you do is get way out in front of it, and get out of your car. Walk over and grab the yellow-line in the middle of the road. Rip it so that you have an end, and carry your end to the nearest wall, then set it down. The robotic vehicle will follow the curved line at full speed, straight into the brick

i do keep up with robotics and ai, religiously following the progress of the field for almost twenty years. and i have read every article i could find on the DARPA race, and kept track of the race on the (awful) Flash/shockwave site. after the race was won, i've almost become burnt out on it, almost not caring to watch the NOVA footage. well, i'm glad i did, because it showed the best inside info on how Stanford's AI and sensor fusion worked. and it compared and contrasted Stanley's AI techniques with Ca

A lot of things seems trivial to implement in theory, but in actuality physical and environmental constraints seem to introduce a whole different ball game. A big congrats to all the teams who entered.

One thing that I noticed from the article is that one of the teams has problems with dust accumulating on the sensors. How would one get rid of this dust, so that you don't recieve incorrect readings?

Many of the teams (including us, small team, but still finalist) had little water spray nozzles. The LADAR would actually have a very specific error code when it was being disrupted, so we triggered on that. We also disregarded all "obstacles" within 1 cm of the sensor (ie: the lense!).

Although software was a big focus, having good mechanical engineers was the key. Keeping stuff cool and free from vibration type failures was a BIG deal.

Honestly, not really. It was so damn dry out there that they water would spray the dust off and dry off in no time. I'd say rarely though did we ever see the water system turn on. Really, only in our mud testing did we ever get major buildup. Those LADAR's were pretty resilient sensors. The sun shining in them was much worse than any dust buildup.

Last Saturday, Digital Village Radio [digitalvillage.org] did an interview with Jason Spingarn-Koff, the filmaker of The Great Robot Race, and Sebastian Thrun, the leader of the winning Team Stanford. Here's a link to the mp3 [digitalvillage.org].

So DARPA funds this to create autonomous supply vehicles, which might work in a traditional battle with clearly drawn front lines and relatively secure transport routes behind the lines.

It seems to me like 21st century warfare is a whole different animal - how hard would it be for a motivated, talented individual to figure out some simple attacks for the navigation systems on these vehicles, and get loads of sweet US munitions delivered to their doorstep? How effective would one of these vehicles be in an urban setting? How easy would it be to create a series of obstacles that would paralyze one of these vehicles?

It's amazing technology, for sure, and the Stanford and CMU teams deserve kudos. I'm just concerned that with the current rush to technological solutions and shift away from "boots on the ground", this technology will be in battle zones far too quickly.

On the other hand, with driver drones you can try all new tactics. Perhaps instead of a single well-established supply line, you can "swarm" the supplies into place with more, smaller vehicles. As for captured munitions, with no driver onboard, a remote destruct function becomes a possibility. Or maybe highly sensitive shipments like munitions will simply be trucked conventionally (by a person). That still leaves a lot of other stuff to move around.

how hard would it be for a motivated, talented individual to figure out some simple attacks for the navigation systems on these vehicles, and get loads of sweet US munitions delivered to their doorstep?

How hard? I would say next to impossible. Tricking the GPS system on board is impossible, while staying alive. You'd have to emulate enough GPS sats to give the vehicle improper coordinates (not only would these Satellite emulators have to work, but they would have to be synchronized properly, don't forg

The word in the robotics community is that there will be another DARPA Grand Challenge, this time focused on urban driving. This should be a significantly harder problem, as if the first one wasn't hard enough!

If I remember correctly, the object sensors on these 'bots can not distinguish between a solid, impassable obstacle and a harmless bunch of scrub that could be driven through. Assuming this is true, couldn't you create a 'wall' out of bedsheets or some other cheap material and box one of these vehicles in very quickly. Once disabled (confused), you could unload the supplies or damage the vehicle.

This is just conjecture based on a half-recollection but I don't thik it would be too difficult to attack a rel

If anyone is really interested in the technical and mathematical side of this stuff, I definitely recommend Probabilistic Robotics [amazon.co.uk] by (among others) Sebastian Thrun, director of the Stanford Artificial Intelligence Lab and leader of the winning team in this race.

Does anyone at DARPA, the Defense Department or any of the universities involved watch movies? Have they not seen the Terminator series? Haven't they read Harlan Ellison? Herman Hesse's Steppenwolf? Is this the start of the war between humans and machines? I think they need to require more reading and humanities credits for scientists and engineers. I can see myself in twenty years running from human hunting humvees in the national forest. What are we starting?

Don't you see? This is the beginnings of a grand scheme to unite all of mankind by creating a common enemy which will attempt to destroy us all. East and West, Communist and Capitalist, Arab and Israeli, Muslim and Christian -- all will have to unite against the evil that will be machines. And after the dust settles, we'll all live happily together. Or something.

Why would they hunt us?What is the issue with the m/c becoming self-aware?For humans, it is essential to fight with others (human or otherwise) to have enough space for survival.So, this is implanted in our genes, that we fight.. or hunt or whatever.

But in robots, unless we specifically code to attack humans, they do *not* have any reason to do that. It is not in their genes*, anyhow.

Even replicating - even that is not in their genes..So there is no isse of them becoming self-aware.

Seriously though, I'd been hoping someone would be putting together something like this (though I'd been expecting it form Discovery or TLC - yay for public television). Fortunately, it is available online [pbs.org] for those of us who missed it.

Obligatory Simpsons Quote:"The wars of the future will not be fought on the battlefield or at sea. They will be fought in space, or possibly on top of a very tall mountain. In either case, most of the actual fighting will be done by small robots. And as you go forth today remember always your duty is clear: To build and maintain those robots. Thank you."-- Military school Commandant's graduation address, "The Secret War of
Lisa Simpson"

This was a very good NOVA documentary. It moved quickly and covered a lot of new ground in a short time, like the algorithms the robots used and the kinds of problems they solved, unlike most documentaries which repackage the same science anecdotes over and over or only discuss philosophy.It wasn't as much the fact that Stanley won the race as how Stanley won the race and the differing approaches of the builders that made it interesting.

I watched this show when it aired last night. I'd actually been looking forward to it quite a bit since seeing a preview for it a week or so ago. Is it just me, or is Nova possibly the best show on television? I don't get so interested in every subject they cover, so I don't watch it all the time, but, I must say, every episode I have seen has been excellent. We could use more television like this, and a lot less American Idol and other BS.There was nothing quite like seeing, for the first time in my life,

I was coming from Utah back to California. We had just stopped in Primm, NV to eat. Just after Primm, we saw what we thought was some crazy guy tearing up the desert after drinking way too much beer. The dust cloud behind this "guy" was incredible - I saw it from miles away. The vehicle was coming towards Primm from the California side and probable a mile off the freeway. As the vehicle past us, that thing was bouncing pretty good. I remember commenting to my girlfriend that that "his" suspension wasn

There were several points made in the program that I hadn't heard elsewhere (and I've been paying attention to the Grand Challenge since the initial press release).

-- The teams get the GPS waypoints a few hours before the race. The waypoints are purposefully vague, so the robots have the choice of driving off a cliff (or into one) while still being within GPS parameters. This is supposed to prevent the race from reducing to "Who can follow GPS the best?" The Red Team had a group of what looked like 20 or 30 people who immediately sat down with the waypoints mapped out on satellite imagery, going through and adding waypoints of their own and adding speed commands for their robots. This seems to me to be a big violation of the spirit of the competition.
-- The Red Team had two entries, which they programmed differently: one more aggressive, the other more conservative (on speed). The faster robot, Highlander, was pulling away from Stanley for the first part of the race, until some unknown issue starting causing problems. Nova didn't say what was wrong, but it looked literally like Highlander was slipping out of gear and rolling back down hills. It _might_ have been doing it on purpose, i.e. a software glitch, but it didn't look that way.
-- One of the Red Team's entries completed the last portion (the hardest portion) of the course with its main sensor non-functional -- it was stuck pointed 90 degrees to the side. This argues even more strongly that the Red Team's vehicles weren't doing much route-finding and were pretty much just following GPS waypoints.

The conclusion I draw from this is that we are still a long way from the DOD's goal of autonomous transport vehicles. In a combat situation, transports need to be able to avoid obstacles put in their way _by the enemy_. The only time during this challenge that the vehicles did anything like this was during the initial trials before the race, and that was very limited. The actual race course was hard -- off-road, dirt, narrow, slippery -- but it didn't have tank traps painted the same color as the dirt they rest on. It didn't have razor-wire barricades, forcing the cars to figure out a route through the bushes around them.

I'm confident that if I had been on the course fifteen minutes before the cars showed up, I could have stalled or disabled all of them. Pile a bunch of bushes across the road and all of them would have stopped. During the trials and race, none of them demonstrated the ability to work around such a very limited obstacle.

All of this is not to minimize what was accomplished. But we're a long way from sitting back sipping champagne while robots do the dirty work of war.

-- One of the Red Team's entries completed the last portion (the hardest portion) of the course with its main sensor non-functional -- it was stuck pointed 90 degrees to the side. This argues even more strongly that the Red Team's vehicles weren't doing much route-finding and were pretty much just following GPS waypoints.

Your point is certainly valid, but also consider that a robot with backup systems that rely on totally different strategies will have a better chance of success when (not "if") something

-- The teams get the GPS waypoints a few hours before the race. The waypoints are purposefully vague, so the robots have the choice of driving off a cliff (or into one) while still being within GPS parameters. This is supposed to prevent the race from reducing to "Who can follow GPS the best?" The Red Team had a group of what looked like 20 or 30 people who immediately sat down with the waypoints mapped out on satellite imagery, going through and adding waypoints of their own and adding speed commands for t

The Red Team's strategy makes sense for accomplishing the goals as expressed by the rules, but the rules do a poor job of representing the actual goal of the military (IMHO). The DARPA staff said on several occasions, GPS alone won't win this race. Well, it didn't, but only because of some sort of unrelated glitch in the Red Team's entry. Highlander would have won if not for the mystery ailment.Agreed that in a military situation you're likely to have extensive pre-planning of the route, but you're not goin

Most interesting stuff. I was glad to see "Stanley" win. The "Highlander" and "Sandstorm" obviously had a lot of tech in them but "Stan" was clearily more reflective of the challange's merit - create a robot that can make decisions. The Red team crammed their vehicles with so much data it was like programming a production line robot. Yeah, it was a robot and a damn impressive one at that, but "Stan" could and had to actually decide things - and it did too. The idea of the laser + video overlay was most bri

I had a close friend at CMU that worked on both of their robots. I got to visit them twice and see their production. H1lander wasn't there the second time because it had a transmission failure. They had to take it to the dealer. Can you imagine an H2 which is completely gutted, loaded with computers and has no steering wheel because it steers itself and having to take it to the dealer.Also, both CMU robotos ran some form of linux with a all of the hardware donated by Intel. I believe they had a 2TB RAI

The most interesting thing I found from the race was the different approaches of the Stanford team who won, and the other teams. Stanford chose to work on the more difficult of the problems, which is the software side of things. They left the hardware of the car to people more adept at such things (Volkswagon). It was interesting to see the other teams focusing on the hardware problem, and leaving the software as less of a problem. The other interesting thing was seeing the different managerial approach

It was a great program, and it prompted me to re-visit the old Slashdot article on this and to look a number of things up. Things that Nova missed:* It mentioned the Gray team being a dark horse, but in reality, they took only about half an hour longer than Stanley. If anything, it was probably even more of a newcomer than Stanley. CMU has been in the robot driving business for a long time (they had neural-net based self-driving vehicles since the early 90's), so for this unknown team to finish so close

I was skeptic robots would ever be able to finish in my old slashdot posts. Apparently they got the sensors right in the 2nd year and five competitors finished. I shoulda stuck around with Red Team year2, but I lost my key to the building and they wouldn't issue me another one.

They didn't finish the race! Out of 23 competitors, 5 finished the race. If anything, they should've focused a bit more on Team Gray and TerraMax, who did finish the race (though TerraMax was disqualified due to time).